The boundary detection algorithm previously described has been implemented, tested, and refined on the DCRT Evans and Sutherland Image Processing Facility. This algorithm performs automated planimetry on light microscopy video images of optically microtomed sections of in vivo Necturus gall bladder cells to provide time histories of cell volume changes. The refined algorithm searches extrema of pixel variances along pin filters orthogonal to guided segments of radial spokes emanating from the cell section centers. Efforts to transport this algorithm to an NHLBI computer system for continuing laboratory use have begun.